Databricks vs Milvus
Side-by-side comparison to help you choose the best tool.
Databricks
paidUnified analytics platform for big data and machine learning workloads.
Visit DatabricksMilvus
freemiumMilvus is a cloud-native, open-source vector database built to handle billions of vectors at enterprise scale. Originally developed at Zilliz and donated to the LF AI & Data Foundation, it powers semantic search, recommendation systems, and AI applications at companies like Walmart and Shopee. Milvus supports multiple index types, GPU acceleration, and a distributed architecture - making it the most scalable open-source vector database available.
| Feature | Databricks | Milvus |
|---|---|---|
| Pricing | paid | freemium |
| Category | Data & Analytics | Data & Analytics |
| Rating | N/A | 4.4 |
| Best For | - | Enterprise engineering teams building billion-scale vector search systems for recommendation engines, semantic search, and AI applications |
| Views | 178,328 | 147 |
| Attribute | Databricks | Milvus |
|---|---|---|
| Pricing Type | paid | freemium ✓ |
| Free Trial | No | No |
| API Available | No | No |
| Mobile App | No | No |
| Rating | N/A | 4.4 ✓ |
| Founded | - | - |
| Team Size | - | - |
| Deployment | - | - |
| Popularity (Views) | 178,328 ✓ | 147 |
Pros
No pros listed.
Cons
No cons listed.
Pros
- Handles the largest vector datasets of any open-source option
- GPU acceleration for ultra-fast indexing
- Strong enterprise adoption and LF AI foundation backing
Cons
- Complex to operate at full distributed scale
- Heavier infrastructure requirements than lighter alternatives
No features listed.
- Billion-scale vector search
- Multiple index types (HNSW, IVF, DiskANN)
- GPU acceleration support
- Distributed cloud-native architecture
- Python, Java & Go SDKs
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